Author: Vikram Elango

Open-source large language models (LLMs) have become popular, allowing researchers, developers, and organizations to access these models to foster innovation and experimentation. This encourages collaboration from the open-source community to contribute to developments and improvement of LLMs. Open-source LLMs provide transparency to the model architecture, training process, and training data, which allows researchers to understand […]

Machine learning (ML) applications are complex to deploy and often require multiple ML models to serve a single inference request. A typical request may flow across multiple models with steps like preprocessing, data transformations, model selection logic, model aggregation, and postprocessing. This has led to the evolution of common design patterns such as serial inference […]

Natural language understanding is applied in a wide range of use cases, from chatbots and virtual assistants, to machine translation and text summarization. To ensure that these applications are running at an expected level of performance, it’s important that data in the training and production environments is from the same distribution. When the data that […]